1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

use std::any::Any;
use std::fmt::{Debug, Display};
use std::hash::{Hash, Hasher};
use std::sync::Arc;

use crate::expressions::column::Column;
use crate::utils::scatter;

use arrow::array::BooleanArray;
use arrow::compute::filter_record_batch;
use arrow::datatypes::{DataType, Schema, SchemaRef};
use arrow::record_batch::RecordBatch;
use datafusion_common::tree_node::{Transformed, TreeNode};
use datafusion_common::{internal_err, not_impl_err, plan_err, Result};
use datafusion_expr::interval_arithmetic::Interval;
use datafusion_expr::sort_properties::ExprProperties;
use datafusion_expr::ColumnarValue;

/// See [create_physical_expr](https://docs.rs/datafusion/latest/datafusion/physical_expr/fn.create_physical_expr.html)
/// for examples of creating `PhysicalExpr` from `Expr`
pub trait PhysicalExpr: Send + Sync + Display + Debug + PartialEq<dyn Any> {
    /// Returns the physical expression as [`Any`] so that it can be
    /// downcast to a specific implementation.
    fn as_any(&self) -> &dyn Any;
    /// Get the data type of this expression, given the schema of the input
    fn data_type(&self, input_schema: &Schema) -> Result<DataType>;
    /// Determine whether this expression is nullable, given the schema of the input
    fn nullable(&self, input_schema: &Schema) -> Result<bool>;
    /// Evaluate an expression against a RecordBatch
    fn evaluate(&self, batch: &RecordBatch) -> Result<ColumnarValue>;
    /// Evaluate an expression against a RecordBatch after first applying a
    /// validity array
    fn evaluate_selection(
        &self,
        batch: &RecordBatch,
        selection: &BooleanArray,
    ) -> Result<ColumnarValue> {
        let tmp_batch = filter_record_batch(batch, selection)?;

        let tmp_result = self.evaluate(&tmp_batch)?;

        if batch.num_rows() == tmp_batch.num_rows() {
            // All values from the `selection` filter are true.
            Ok(tmp_result)
        } else if let ColumnarValue::Array(a) = tmp_result {
            scatter(selection, a.as_ref()).map(ColumnarValue::Array)
        } else {
            Ok(tmp_result)
        }
    }

    /// Get a list of child PhysicalExpr that provide the input for this expr.
    fn children(&self) -> Vec<&Arc<dyn PhysicalExpr>>;

    /// Returns a new PhysicalExpr where all children were replaced by new exprs.
    fn with_new_children(
        self: Arc<Self>,
        children: Vec<Arc<dyn PhysicalExpr>>,
    ) -> Result<Arc<dyn PhysicalExpr>>;

    /// Computes the output interval for the expression, given the input
    /// intervals.
    ///
    /// # Arguments
    ///
    /// * `children` are the intervals for the children (inputs) of this
    ///   expression.
    ///
    /// # Example
    ///
    /// If the expression is `a + b`, and the input intervals are `a: [1, 2]`
    /// and `b: [3, 4]`, then the output interval would be `[4, 6]`.
    fn evaluate_bounds(&self, _children: &[&Interval]) -> Result<Interval> {
        not_impl_err!("Not implemented for {self}")
    }

    /// Updates bounds for child expressions, given a known interval for this
    /// expression.
    ///
    /// This is used to propagate constraints down through an expression tree.
    ///
    /// # Arguments
    ///
    /// * `interval` is the currently known interval for this expression.
    /// * `children` are the current intervals for the children of this expression.
    ///
    /// # Returns
    ///
    /// A `Vec` of new intervals for the children, in order.
    ///
    /// If constraint propagation reveals an infeasibility for any child, returns
    /// [`None`]. If none of the children intervals change as a result of propagation,
    /// may return an empty vector instead of cloning `children`. This is the default
    /// (and conservative) return value.
    ///
    /// # Example
    ///
    /// If the expression is `a + b`, the current `interval` is `[4, 5]` and the
    /// inputs `a` and `b` are respectively given as `[0, 2]` and `[-∞, 4]`, then
    /// propagation would return `[0, 2]` and `[2, 4]` as `b` must be at least
    /// `2` to make the output at least `4`.
    fn propagate_constraints(
        &self,
        _interval: &Interval,
        _children: &[&Interval],
    ) -> Result<Option<Vec<Interval>>> {
        Ok(Some(vec![]))
    }

    /// Update the hash `state` with this expression requirements from
    /// [`Hash`].
    ///
    /// This method is required to support hashing [`PhysicalExpr`]s.  To
    /// implement it, typically the type implementing
    /// [`PhysicalExpr`] implements [`Hash`] and
    /// then the following boiler plate is used:
    ///
    /// # Example:
    /// ```
    /// // User defined expression that derives Hash
    /// #[derive(Hash, Debug, PartialEq, Eq)]
    /// struct MyExpr {
    ///   val: u64
    /// }
    ///
    /// // impl PhysicalExpr {
    /// // ...
    /// # impl MyExpr {
    ///   // Boiler plate to call the derived Hash impl
    ///   fn dyn_hash(&self, state: &mut dyn std::hash::Hasher) {
    ///     use std::hash::Hash;
    ///     let mut s = state;
    ///     self.hash(&mut s);
    ///   }
    /// // }
    /// # }
    /// ```
    /// Note: [`PhysicalExpr`] is not constrained by [`Hash`]
    /// directly because it must remain object safe.
    fn dyn_hash(&self, _state: &mut dyn Hasher);

    /// Calculates the properties of this [`PhysicalExpr`] based on its
    /// children's properties (i.e. order and range), recursively aggregating
    /// the information from its children. In cases where the [`PhysicalExpr`]
    /// has no children (e.g., `Literal` or `Column`), these properties should
    /// be specified externally, as the function defaults to unknown properties.
    fn get_properties(&self, _children: &[ExprProperties]) -> Result<ExprProperties> {
        Ok(ExprProperties::new_unknown())
    }
}

impl Hash for dyn PhysicalExpr {
    fn hash<H: Hasher>(&self, state: &mut H) {
        self.dyn_hash(state);
    }
}

/// Returns a copy of this expr if we change any child according to the pointer comparison.
/// The size of `children` must be equal to the size of `PhysicalExpr::children()`.
pub fn with_new_children_if_necessary(
    expr: Arc<dyn PhysicalExpr>,
    children: Vec<Arc<dyn PhysicalExpr>>,
) -> Result<Arc<dyn PhysicalExpr>> {
    let old_children = expr.children();
    if children.len() != old_children.len() {
        internal_err!("PhysicalExpr: Wrong number of children")
    } else if children.is_empty()
        || children
            .iter()
            .zip(old_children.iter())
            .any(|(c1, c2)| !Arc::ptr_eq(c1, c2))
    {
        Ok(expr.with_new_children(children)?)
    } else {
        Ok(expr)
    }
}

/// Rewrites an expression according to new schema; i.e. changes the columns it
/// refers to with the column at corresponding index in the new schema. Returns
/// an error if the given schema has fewer columns than the original schema.
/// Note that the resulting expression may not be valid if data types in the
/// new schema is incompatible with expression nodes.
pub fn with_new_schema(
    expr: Arc<dyn PhysicalExpr>,
    schema: &SchemaRef,
) -> Result<Arc<dyn PhysicalExpr>> {
    Ok(expr
        .transform_up(|expr| {
            if let Some(col) = expr.as_any().downcast_ref::<Column>() {
                let idx = col.index();
                let Some(field) = schema.fields().get(idx) else {
                    return plan_err!(
                        "New schema has fewer columns than original schema"
                    );
                };
                let new_col = Column::new(field.name(), idx);
                Ok(Transformed::yes(Arc::new(new_col) as _))
            } else {
                Ok(Transformed::no(expr))
            }
        })?
        .data)
}

pub fn down_cast_any_ref(any: &dyn Any) -> &dyn Any {
    if any.is::<Arc<dyn PhysicalExpr>>() {
        any.downcast_ref::<Arc<dyn PhysicalExpr>>()
            .unwrap()
            .as_any()
    } else if any.is::<Box<dyn PhysicalExpr>>() {
        any.downcast_ref::<Box<dyn PhysicalExpr>>()
            .unwrap()
            .as_any()
    } else {
        any
    }
}